lognat0704/diffusion-loras

Qwen-Image-Edit LoRAs

A collection of LoRA adapters I trained for Qwen-Image-Edit, focused on pose control and subject consistency in image editing.

The adapters were trained on a mix of collected reference images and synthetic images generated with the Qwen image model.

Adapters

File	Purpose	Rank
qwen-image-edit/multipose_v50_rank96.safetensors	Multi-pose control (latest)	96
qwen-image-edit/multipose_v49h_rank96.safetensors	Multi-pose control (prior revision)	96
qwen-image-edit/qwen_Image_male.safetensors	Male subject conditioning	-

Usage

Load an adapter on top of the Qwen-Image-Edit pipeline with diffusers:

from diffusers import QwenImageEditPipeline
import torch

pipe = QwenImageEditPipeline.from_pretrained(
    "Qwen/Qwen-Image-Edit", torch_dtype=torch.bfloat16
).to("cuda")

pipe.load_lora_weights(
    "lognat0704/diffusion-loras",
    weight_name="qwen-image-edit/multipose_v50_rank96.safetensors",
)

# image = pipe(prompt=..., image=...).images[0]

Notes

• Adapters are rank-96 unless noted.
• The multipose series iterates on pose-conditioning quality; v50 is the most recent.